Detection of β-amyloid positivity in Alzheimer's Disease Neuroimaging Initiative participants with demographics, cognition, MRI and plasma biomarkers

Abstract

In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid₄₂ or the β-amyloid₄₂/β-amyloid₄₀ ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid₄₂/β-amyloid₄₀, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid₄₂/β-amyloid₄₀ as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid₄₂/β-amyloid₄₀ may be improved by age and APOE genotype.

Keywords: Alzheimer’s; MRI; PET; plasma; β-amyloid.

Graphical Abstract

Figure 1

Plasma (A) Aβ₄₂/Aβ₄₀, (B) NfL concentrations and (C) p-tau181 concentrations categorized by clinical diagnosis and CSF Aβ-positivity. Plasma Aβ₄₂/Aβ₄₀ data was available for 173 individuals (Aβ− CU, n = 50; Aβ+ CU, n = 37; Aβ− CI, n = 40; Aβ+ CI, n = 46). Plasma p-tau181 and NfL data included 852 individuals (Aβ− CU, n = 224; Aβ+ CU, n = 109; Aβ− CI, n = 230; Aβ+ CI, n = 289). Unpaired two-samples t-test uncorrected significance levels at ****P < 0.00001; ***P < 0.0001; **P < 0.001; ns: P ≥ 0.5. CU, cognitively unimpaired elderly; CI, elderly individuals with mild cognitive impairment.

Figure 2

Receiver-operating characteristic (ROC) analysis of Aβ positivity prediction in an ADNI cohort of (A) cognitively unimpaired (CU) and (B) cognitively impaired (CI) elderly individuals. Optimized ROC curves for classifiers constructed separately and jointly with demographic information (age, sex and years of education), APOE, clinical scores, plasma biomarkers (Aβ₄₂/Aβ₄₀, p-tau181 and NfL), and structural MRI-score when predicting Aβ-positivity using florbetapir PET as the ground truth in the ADNI study (n = 333 CUs and n = 519 CIs). To assess the added value of each class of variables (i.e. clinical, plasma and MRI classes), additional RF classifiers were constructed from (i) each plasma marker alone, (ii) each plasma marker jointly with clinical features, (iii) MRI-score jointly with clinical features and (iv) each plasma marker jointly with clinical features and MRI-score. Models including plasma Aβ₄₂/Aβ₄₀ were tested and validated in a cohort of n = 87 CUs and n = 86 CIs due to limited availability of plasma Aβ₄₂/Aβ₄₀ data. Error bars indicate union of 95% CIs from cross-validation iterations.

Figure 3

Classifier performance metrics of Aβ positivity prediction in (A) cognitively unimpaired (CU) individuals and B) individuals with mild cognitive impairment (CI). Area under the curve (AUC) estimates with ±2 × standard variation error bars from cross-validation iterations are shown for classifiers constructed separately and jointly with demographic information (age, sex and years of education), APOE, clinical scores, plasma biomarkers (Aβ₄₂/Aβ₄₀, p-tau181 and NfL) and structural MRI-score when predicting Aβ-positivity using florbetapir PET as the ground truth in the ADNI study (n = 333 CUs and n = 519 CIs). To assess the added value of each class of variables (i.e. clinical, plasma and MRI classes), additional RF classifiers were constructed from (i) each plasma marker alone, (ii) each plasma marker jointly with clinical features, (iii) MRI-score jointly with clinical features and (iv) each plasma marker jointly with clinical features and MRI-score. Models including plasma Aβ₄₂/Aβ₄₀ were tested and validated in a cohort of n = 87 CUs and n = 86 CIs due to limited available of plasma Aβ₄₂/Aβ₄₀ data. Error bars indicate union of 95% CIs from cross-validation iterations.